Collaborative Research: ARTS: A modern taxonomy for Cercospora (Mycosphaerales, Ascomycota) and a multiomics interactive data platform for hypothesis testing

Humans are directly dependent on plants for the majority of caloric intake and indirectly through the ecosystem services they provide. Fungi are among the most economically important plant pathogens in both agricultural and non-agricultural populations, influencing the structure and productivity of plant populations. Mitigating disease caused by these fungal pathogens requires an accurate understanding of species richness, their distribution, their relationships to other pathogenic species, the plant species they infect, and the genetic features that allow them to be pathogens. Cercospora species are fungi that are known to cause disease on nearly every major crop plant in the world, including important staples (e.g. rice). However, these fundamental questions - How many species are there? Where are they found? What host species do they impact? What genetic features allow them to cause disease on some hosts and not others? - need to be addressed in a modern context to enable research into mitigating their impacts. The goals of the project are to answer these questions and develop an accessible data interface that will allow other researchers to leverage this information to ultimately mitigate disease. While fungi have long been overlooked, training will be provided to high school, undergraduate, and graduate students to be the next generation of fungal biologists helping to solve global issues caused by fungi. Understanding how fungi impact plant populations requires a natural classification scheme that can be cross-referenced with ecological, morphological, geographical, or any trait-based information to better understand the life history of individual species. This information has enormous ecological and economic impacts because fungi are the most economically important plant pathogens. The genus Cercospora is among the most speciose genera of fungi, but our understanding of species limits and evolutionary relationships is constrained by a lack of accessible data. This project will address this gap by (i) producing a phylogenomic-based revision of the genus Cercospora and assessing global species richness of one of the most ubiquitous and economically important foliar fungi on the planet, (ii) characterize genome and transcriptome evolution across the genus, and (iii) produce an integrative database collating metadata that facilitates hypothesis testing in a phylogenetic framework. Data will be collected from type specimens, field work conducted in North America, and modern collections for genomic/transcriptomic studies developed. New species will be described, and barcode loci for the cost-effective integration of collections from around the world developed. A framework for integrating multiple data layers through relational databases that are linked to a hierarchical phylogenetic structure will be made available through a dedicated web interface to researchers interested in exploring hypotheses in Cercospora evolution, identifying new Cercospora isolates and species, expanding on existing data or adding new data layers. This interface will allow a broad group of users, from molecular biologists to applied plant pathologists, to explore hypotheses and develop solutions to fundamental and applied problems. The next generation of taxonomists in mycology, comparative genomics, and bioinformatics will be trained to help mitigate the impacts of fungal plant pathogens. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2616151 | Program: 01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Ignazio Carbone | Institution: North Carolina State University, RALEIGH, NC | Award Amount: $600,163 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2616151 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2616151.html